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Advances in Fuzzy Systems
Volume 2018, Article ID 4279236, 9 pages
https://doi.org/10.1155/2018/4279236
Research Article

Optimization of Risk and Return Using Fuzzy Multiobjective Linear Programming

Department of Mathematics, Maulana Azad National Institute of Technology, Bhopal (MP), India

Correspondence should be addressed to Darsha Panwar; moc.liamg@ahsrad.rawnap

Received 11 May 2018; Revised 25 July 2018; Accepted 14 August 2018; Published 3 September 2018

Academic Editor: Zeki Ayag

Copyright © 2018 Darsha Panwar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Stock selection poses a challenge for both the investor and the finance researcher. In this paper, a hybrid approach is proposed for asset allocation, offering a combination of several methodologies for portfolio selection, such as investor topology, cluster analysis, and the analytical hierarchy process (AHP) to facilitate ranking the assets and fuzzy multiobjective linear programming (FMOLP). This paper considers some important factors of stock, like relative strength index (RSI), coefficient of variation (CV), earnings yield (EY), and price to earnings growth ratio (PEG ratio), apart from the risk and return and stocks which are included within these same factors. Employing fuzzy multiobjective linear programming, optimization is performed using seven objective functions viz., return, risk, relative strength index (RSI), coefficient of variation (CV), earnings yield (EY), price to earnings growth ratio (PEG ratio), and AHP weighted score. The FMOLP transforms the multiobjective problem to a single objective problem using the “weighted adaptive approach” in which the weights are calculated by AHP or choices by the investors. The FMOLP model permits choices in solution.